About
Josh Von Korff is a Lecturer in the Faculty of Computing & Data Sciences (CDS) in support of the online MS in Data Science (OMDS) Program. Prior to joining BU, Josh was a data scientist in industry for three years, including one year as a data science consultant.Can you share a little about your academic background and what led you to specialize in your current field?
Most recently, I have been a data scientist in industry. I enjoy data science partly because it is an application of mathematics to the real world. I like math, and data science is an extremely useful way to apply math. Data science helps businesses and academics to achieve their goals. For this reason, over the course of my career I’ve moved toward more practice disciplines like data science.
I have studied and published in a number of topics. I’ve written about sequences in the field of combinatorics and entanglement and information in the field of theoretical quantum computing. I worked on the Stardust@home project to distribute the detection of interstellar dust grains among many volunteers. My PhD dissertation involved a volunteer computing project: Astropulse. In this project, I searched for transient (non-repeating) radio signals from various sources - such as pulsars or exploding black holes.
Later, I have studied physics education research - a field in which we study how to teach physics better. I studied how to explain calculus to students in the context of physics, including layers (Riemann sums) and representations (tables, equations, graphs, and diagrams). I also studied infinitesimals used for integration. I investigated different ways of teaching physics labs, such as the practice of revisiting the same question from different perspectives.
What is your involvement with the OMDS program?
I am a lecturer teaching the AI for Leaders and Data Science Capstone courses, in which students will find and explore datasets, then use models to select and investigate questions about the data. Students will address how these questions are important in industry and important to them personally.
I am also teaching the Mathematical Foundations of Data Science course, and the Experimental Design and Causality course.
What are the main focuses of your current research, and what impact do you hope to achieve in your field?
As a lecturer, I hope to prepare students for work in industry or academia. I would like students to develop:1. A conceptual understanding of data science and statistics ideas.
2. An ability to clean and manipulate data.
3. An ability to perform exploratory data analysis.
4. An ability to implement data science models in code.
5. An ability to visualize data.
6. An ability to measure and report on the performance of models.
7. An understanding of data ethics.
8. Practice with collaboration and teamwork.
All of these goals are interrelated with each other - and with the other modules in the program. I have studied education for many years, but there is always room to grow and improve; it is important to me to continue to grow as a teacher.
Which courses do you teach at BU Computing & Data Sciences, and what do you enjoy most about teaching these subjects?
In the current semester, I am teaching the first semester of the AI for Leaders/Capstone sequence. My favorite part of this first semester is that students will get a chance to perform their own research in the sense of locating and analyzing datasets of their choice. It’s by engaging in a project that students will learn about the practice of data science.Which recent developments in your field do you find particularly exciting? How have they influenced your work and teaching?
Data science education is a newly important discipline. The Journal of Statistics Education changed its name to the Journal of Statistics and Data Science Education in 2021. I am excited to be present near the beginning of this relatively new field and to apply it to my teaching. I believe that there is a continuity between my experience in physics education research with the field of data science education. For example, the value of student participation and interactive engagement is important in both disciplines.